Adaptive Intrusion Detection System Based on Agent and Data Mining

Intrusion detection system is an essential component of network security protection mechanisms. Most intrusion detection system can not adapt the variation of network environment. Aiming at this problem, an adaptive strategy that composed of condition space and strategy space is proposed. The condition space describes the network environment and the strategy space describes the strategy. There is an exclusive strategy corresponds to a certain environment state in condition space. On the base of the adaptive strategy, an adaptive intrusion detection system based on agent and data mining is designed. The simulation experiments indicate that the adaptive strategy is effective.     

Fuzzy Clustering Theory for Analyzing Intrusion Detection Data

Intrusion detection system is an important component of the computer and information security framework. Its main goal is to differentiate between normal activities of the system and behaviors that can be classified as suspicious or intrusive, and its main challenge is to efficiently detect intrusion detection behaviors for reducing false positive rate and false negative rate. In view of the disadvantages of the existing intrusion detection methods, fuzzy c-means(FCM) clustering method is used to analyze intrusion detection data in order to detect anomaly network behavior patterns. Experimental results on the CUP99 data set data show that this method can not only feasible but also improve the accuracy and efficiency.     

Intrusion Detection Technology in Ad Hoc Network

With the rapid development of wireless network and mobile computing,the security of network becomes more important.As one of wireless mobile network,mobile Ad hoc network has new vulnerabilities that do not exist in a fixed wired network,and is susceptible to attacks.This paper introduces some methods which used in intrusion detection system and provides a new model of system based on multi-layer integrated distributed technology,especially recommend the protocol analyzing method in this system.     

陆地生态系统有机碳储量和碳排放的研究进展

陆地生态系统土壤有机碳储量和土壤呼吸的微小变化,会引起大气CO2浓度的巨大变化以及全球碳循环的明显改变,从而引起全球气候的巨大变化。提高SOC储量、减少土壤CO2排放对减缓大气CO2浓度升高具有重要意义。笔者根据国内外文献数据资料,综合分析陆地生态系统土壤有机碳储量和土壤呼吸的研究进展,并对最近土壤呼吸影响因素的研究热点因子,如土壤温度、土壤水分、大气降水和耕作等进行分析讨论,指出陆地生态系统碳循环研究中应重点加强土壤呼吸的机理、土壤呼吸影响因素、土壤呼吸模型、土壤固碳措施、减排对策的研究。     

渔业船联网工程体系应用现状分析

渔业船联网工程是通过在渔船上搭载信息感知、处理和传输装备,从而实现船与船、船与岸之间的信息交换和智能化服务,在渔业生产、海上通信、安全管理、渔政执法及海洋探测等领域具有的重要科学意义和实用价值。本文分析了渔业船联网工程体系的应用现状及演化趋势,详细总结了渔业船联网感知层、传输层和应用层的国内外现状及发展趋势,梳理了所涉及的关键技术和科学问题。围绕渔船探测、海洋通信、数据融合与挖掘等重大需求,分析了中国渔业船联网发展在基础研究、平台建设、尖端技术、装备工程、标准体系等方面存在的主要问题与障碍,指出了中国渔业船联网工程体系科技创新发展对策,提出了以“突破关键技术、研发核心装备、构建基础平台、形成创新能力”为目标、以“探索期、部署期、拓展期”为路线的系统工程发展建议。     

区域粮食安全度量研究 ——以重庆市万盛区石林镇为例

随着经济的快速发展,工业化、城镇化的快速推进,粮食安全问题日益突出,对区域粮食安全进行度量研究,进而建立起合理的区域粮食安全度量模型尤为重要。文章基于粮食产量波动系数、最小人均耕地面积、耕地压力指数建立了综合区域粮食安全度量模型,并以重庆市万盛区石林镇为例,进行动态研究及预测,结果表明：石林镇粮食安全系数呈下降趋势,在未来5年内还有恶化的趋势。针对动态分析及预测结果,提出了相应的调控措施。     

农田土壤重金属污染监测技术发展趋势

农田土壤作为人类各种粮食作物赖以生存的自然环境,其生态环境问题一直是环境科学界研究的热点。随着世界工业化和城市化进程整体快速推进,环境污染日益加剧,土壤的重金属污染甚为严重,为了更好地对土壤环境进行监测评估和控制,研究和开发有效的检测土壤重金属方面的仪器和监测方法是十分必要的。为此,简述了国内外常用的实验室监测农田土壤重金属污染的技术及其监测局限性,同时重点介绍了基于激光诱导击穿光谱法和磁化率法这2种现场快速监测技术的研究发展现状及对其未来发展需要解决的关键问题进行了探讨。最后对比分析了实验室及现场快速这2种监测方式自身的优劣势,进而探讨了未来区域农田土壤重金属污染监测技术的发展趋势。     

区块链技术及其在农产品质量安全追溯应用的研究进展

农产品质量安全是一个备受关注的公共卫生问题,追溯应用已成为保障农产品质量安全的有效手段。确保溯源数据的真实性和安全性,成为追溯应用研究的重点和亟需解决的问题。区块链是一个综合多种技术并确保完全去中心化点对点系统完备性的完整技术方案,具有去中心化、透明化、去信任和数据不可篡改等优点,不受传统中心式技术的制约,在农产品质量安全追溯应用上有很大的发展空间。文章概述了区块链技术的基础架构、关键技术及其在追溯应用上的特点,以及区块链技术和农产品质量追溯的内在关系;通过分析基于公有链、联盟链和改良模式的农产品质量安全追溯研究进展和技术特点,总结了区块链技术在农产品质量安全追溯研究中存在的问题,结合区块链发展趋势,提出了注重横向技术融合、加强监测数据信息上链、建立农产品追溯激励惩罚机制等研究展望。     

农业信息资源上数据挖掘的应用

【研究目的】通过应用数据挖掘技术解决农业信息领域“信息爆炸,但知识贫乏的问题”,提高农业资源的利用率。【方法】学习分析农业信息以及数据挖掘技术的特点。【结果】提出数据挖掘技术应用于农业具体领域的建议并架构农业数据挖掘系统,根据数据挖掘的流程及其相关技术,设计出具有3层机构的农业数据挖掘系统,并突出阐述每层的功能,其次介绍农业挖掘工具集的特点。【结论】以农业科学数据网数据库为背景,致力于在现有海量数据存储和强大计算能力的基础上,通过数据挖掘技术来进一步提升农业信息服务水平。     

Intrusion Detection Based on Adaptive Immune Classifier

The distribution properties of the normally data and anomaly data in the network connectivity features have huge differences ; therefore, there exist the low rate of detection and false positive rate problem for the traditional classifier which is applied to the network intrusion detection. An adaptive classifier based on the artificial immune cluster is presented. The new classifier adopts multi -granularities idea and it effectively eliminates the inconsistency between the classification algorithm and the clustering algorithm. Through the classification of the data sets in real variety of network intrusion data sets, experimental results show that the classifier has high detection rate and low false positive rate; it has better classification performance and generalization ability than RBF and BP classifiers.     

农业信息技术在小麦育种中的应用研究

小麦作为我国三大粮食作物之一,其市场需求量不断增加。随着气候等因素变化,小麦产量及品质将受到严峻考验,因此需要更为优良的新品种出现。现阶段我国小麦育种仍主要以传统育种技术为主,而凭借育种家经验,从海量育种群体中筛选获得高产、多抗、优质新品种的难度越来越大。因此,有效提升育种效率变得极为迫切。随着农业信息技术在育种中应用的迅猛发展,无损预测预报与进程信息化管理等高效育种成为可能。本文从育种进程管理、数据采集、综合评判决策、种质资源信息化管理方面介绍国内外信息技术在小麦育种中的研究进展,分析信息化育种的需求和存在的主要问题,并对其应用前景进行展望。     

大数据与安全可视化

IT技术的飞速发展开启了大数据时代。海量的数据信息带来更多的数据价值的同时,各类安全问题也随之而来。通过数据可视化技术能够帮助充分全面并且及时地找出系统中可能存在的安全威胁,评估系统安全,保证基础设施的安全。研究从数据角度出发,结合大数据的特征对安全数据进行分类,并对当前已存在的针对不同安全数据进行可视化的工具及技术进行总结,使得能够将已成熟的数据安全可视化技术用于大数据安全的研究,最后对未来的发展趋势进行了展望。     

Clustering Detection Algorithms for Network Intrusions

Traditional abnormal detection methods need a reference model with a profile of normal action, but building the character profile and specifying threshold of abnormal alarm are difficult. So this paper puts forward intrusion detection in combination with clustering and data processing . This algorithm comes true dynamicly updating the center of cluster and the biggest distance within cluster with fast convergence. The effect is better with the help of pre-processing the data. By means of simulated experiments, this algorithm is proved feasible and efficient for unknown intrusion detection.     

Distributed Data Mining on the Grid

Distributed data mining(DDM) is widely used in industrial,scientific and commercial applications to analyze large datasets maintained over geographically distributed sites,which makes DDM a major research issue on(today's) data mining field.This paper discusses the disadvantages of existing DDM systems,puts forward a service-oriented architecture for DDM on the grid and describe the process of mining under this framework.In the proposed,serviceoriented,cross-platform framework,the mining algorithm and distributed data sets are packed into the Web Service Resources(WS-Resource) respectively,which can cooperate to perform DDM as required dynamically.Finally,a grid based on local area network was built with Globus Toolkit 4.0 and take an example of association rule mining to illustrate how to work with the proposed architecture.     

Research Progress on the Extraction Methods of Chlorogcnic Acid from FLOS LONICERAE JAPONICAE

FLOS LONICERAE JAPONICAE,the dry buds of Lonicera japonica Thunb.,is rich in various effective components such as volatile oils,flavonoids,chlorogenic acids and triterpenes. Among them,chlorogenic acid is one of the components having the strongest pharmacological activity. At present,chlorogenic acid content is usually used as the index for the quality evaluation of Traditional Chinese Medicine and the detection of effective components in Traditional Chinese Medicine. Therefore,the extraction technology for chlorogenic acid from FLOS LONICERAE JAPONICAE becomes particularly important. In this research,reports on the extraction methods of chlorogenic acid from FLOS LONICERAE JAPONICAE since 1999 were reviewed. The problems in the extraction technologies were analyzed; and the latest research trends were introduced,aiming at providing references for the in-depth research in future.     

circRNA的生物学功能及其在家畜动物上的研究进展

环状RNA(circRNA)是一类内源性的环状非编码RNA。目前circRNA的研究主要集中在癌症、肿瘤等方面,在家畜动物中的研究较少且主要集中在circRNA的信息挖掘。本文总结了circRNA的生成方式、分类、研究方法及生物学功能等方面内容,归纳了其在家畜动物肌肉发育、脂肪沉积等方面的研究进展,分析总结了目前家畜动物circRNA研究中存在的问题,并对其未来的研究方向进行了展望。     

应用土壤圆锥指数仪评估阜新海州矿排土场复垦工程效果

在矿区土地复垦工作中,如何获取合适的土壤特征指标对于提高复垦质量以及复垦效果评估都有着重要的意义。以阜新海州露天矿排土场复垦工程为研究对象,应用新型土壤圆锥指数仪对复垦土壤压实度进行测量,结合GPS信息、GIS技术及统计学方法对数据进行分析,研究土壤圆锥指数方法在评估矿区土壤复垦效果中应用的可行性。通过对排土场覆土复垦区7个地块264个采样点的测量试验,数据分析结果表明,覆土工程5年后,89%以上测量区域的土层厚度达到北方常见农作物生长需求。研究表明,土壤圆锥指数作为评估矿区土地复垦工程一项参数指标具有较强的可行性,但具有一定的片面性,需与其他理化参数相结合,才能更全面地评价矿区复垦效果。     

Repeated game theory intrusion detection model for the Internet of Things

The existing security methods cannot be applied to the Internet of Things due to the defects of communication nodes. To solve this problem, an intrusion detection model based on repeated game theory is presented. A repeated game model algorithm for detecting malicious nodes is built, and the algorithm of Quantal Response Equilibrium (QRE) is used for optimizing the model and making results reach the Nash equilibrium. Moreover, a common punishment strategy is introduced to improve the success of transfer data in this model. The results of the simulation represent that this model can restrain malicious nodes attacking effectively and improve the efficiency of network.     

Application of Web Agent in Spatial Mining Framework

Information available from the Web is unorganized,multi-model and constantly changing and being updated.Therefore,information becomes more difficult to collect ,filter and evaluate. An agent-based framework to support spatial data mining is described. It makes use of three types of agents: Collect agents, Coordinate agents and Query/Mining agents. And then the implementation model is given.     

甜菜基因工程研究进展及其展望

甜菜基因工程是目前甜菜研究领域的热门课题之一,目前已取得一定研究进展,其基本思路是通过分子生物学手段和转基因技术来获得具有优良性状的甜菜新品种（系）。从植物基因工程在甜菜中的应用、转基因研究方法、安全性评价等几个方面对甜菜基因工程研究的近期成果进行了综述,并分析了转基因甜菜研究过程中存在的问题及其研究展望。